The ability to create geotagged photos enables people to share their personal experiences as tourists at specific locations and times. Assuming that the collection of each photographer's geotagged photos is a sequence of visited locations, photo-sharing sites are important sources for gathering the location histories of tourists. By following their location sequences, we can find representative and diverse travel routes that link key landmarks. In this paper, we propose a travel route recommendation method that makes use of the photographers' histories as held by Flickr. Recommendations are performed by our photographer behavior model, which estimates the probability of a photographer visiting a landmark. We incorporate user preference and present location information into the probabilistic behavior model by combining topic models and Markov models. We demonstrate the effectiveness of the proposed method using a real-life dataset holding information from 71,718 photographers taken in the United States in terms of the prediction accuracy of travel behavior.
Description
Travel route recommendation using geotags in photo sharing sites
%0 Conference Paper
%1 kurashima2010travel
%A Kurashima, Takeshi
%A Iwata, Tomoharu
%A Irie, Go
%A Fujimura, Ko
%B International Conference on Information and Knowledge Management (CIKM)
%C New York, NY, USA
%D 2010
%I ACM
%K diss geo inthesis photo predicition recommendation route spatial traverl
%P 579--588
%R 10.1145/1871437.1871513
%T Travel Route Recommendation Using Geotags in Photo Sharing Sites
%U http://doi.acm.org/10.1145/1871437.1871513
%X The ability to create geotagged photos enables people to share their personal experiences as tourists at specific locations and times. Assuming that the collection of each photographer's geotagged photos is a sequence of visited locations, photo-sharing sites are important sources for gathering the location histories of tourists. By following their location sequences, we can find representative and diverse travel routes that link key landmarks. In this paper, we propose a travel route recommendation method that makes use of the photographers' histories as held by Flickr. Recommendations are performed by our photographer behavior model, which estimates the probability of a photographer visiting a landmark. We incorporate user preference and present location information into the probabilistic behavior model by combining topic models and Markov models. We demonstrate the effectiveness of the proposed method using a real-life dataset holding information from 71,718 photographers taken in the United States in terms of the prediction accuracy of travel behavior.
%@ 978-1-4503-0099-5
@inproceedings{kurashima2010travel,
abstract = {The ability to create geotagged photos enables people to share their personal experiences as tourists at specific locations and times. Assuming that the collection of each photographer's geotagged photos is a sequence of visited locations, photo-sharing sites are important sources for gathering the location histories of tourists. By following their location sequences, we can find representative and diverse travel routes that link key landmarks. In this paper, we propose a travel route recommendation method that makes use of the photographers' histories as held by Flickr. Recommendations are performed by our photographer behavior model, which estimates the probability of a photographer visiting a landmark. We incorporate user preference and present location information into the probabilistic behavior model by combining topic models and Markov models. We demonstrate the effectiveness of the proposed method using a real-life dataset holding information from 71,718 photographers taken in the United States in terms of the prediction accuracy of travel behavior.},
acmid = {1871513},
added-at = {2017-02-08T17:45:49.000+0100},
address = {New York, NY, USA},
author = {Kurashima, Takeshi and Iwata, Tomoharu and Irie, Go and Fujimura, Ko},
biburl = {https://www.bibsonomy.org/bibtex/21d0e2e5354e27e9ae45a41272cf29987/becker},
booktitle = {International Conference on Information and Knowledge Management (CIKM)},
description = {Travel route recommendation using geotags in photo sharing sites},
doi = {10.1145/1871437.1871513},
interhash = {b43ae0b4f91551ffd6fb88f3cbdf8de8},
intrahash = {1d0e2e5354e27e9ae45a41272cf29987},
isbn = {978-1-4503-0099-5},
keywords = {diss geo inthesis photo predicition recommendation route spatial traverl},
location = {Toronto, ON, Canada},
numpages = {10},
pages = {579--588},
publisher = {ACM},
series = {CIKM '10},
timestamp = {2017-12-20T18:41:36.000+0100},
title = {Travel Route Recommendation Using Geotags in Photo Sharing Sites},
url = {http://doi.acm.org/10.1145/1871437.1871513},
year = 2010
}